Dear list,
I'm trying to fit a mixed-effects model to a problem that includes:
a continuous response variable (mean jumped distance by 17 species of
frogs) in 3 different arenas and under 2 types of stimuli. So, it's a kind
of two-way ANOVA design. I have the species phylogeny and prepared its
inverse:
treeAinv<-inverseA(phylo,nodes="TIPS",scale=TRUE)$Ainv
I included the following priors:
prior = list(R = list(V = 1, fix = 1), G=list(G1=list(V=1, nu=0.02)))
and the model:
model1<-MCMCglmm(mean_distance~type_arena*type_of_stimulus,
random=~Specie, data=df_spe, family="gaussian",
ginverse = list(Specie=treeAinv), nodes="ALL",
prior=prior, nitt=300000, burnin=25000, thin = 100, verbose=FALSE)
which seems to converge well (heidel.diag p-value = 0.428), ESS greater
than 1000 for both random and fixed effects.
My question is: how can I incorporate intraspecific variation in the jumped
distance? I have the standard error of the distance and tried to make the
model as:
random=~Species+ us(1+se_distance):Species
but I keep getting an error about prior specification:
Error in MCMCglmm(mean_distance ~ type_arena * type_og_stimulus, random =
~Specie + :
prior$G has the wrong number of structures
Thank you in advance,
Diogo
--
*Diogo B. Provete, PhD.*
FAPESP Post-doctoral fellow
Department of Environmental Sciences
Centre for Sciences and Technologies for Sustainability
Federal University of São Carlos
Sorocaba
Gothenburg Global Biodiversity Centre
Box 462 SE-405 30
Göteborg, Sverige
diogoprovete.weebly.com
Cell phone: +5515981022137
Skype: diogoprovete
Editor: Amphibia-Reptilia | Biodiversity Data Journal
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